Cargando…
Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study
BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241730/ https://www.ncbi.nlm.nih.gov/pubmed/35948741 http://dx.doi.org/10.1007/s00392-022-02071-6 |
_version_ | 1785054052659232768 |
---|---|
author | Tilly, Martijn J. Lu, Zuolin Geurts, Sven Ikram, M. Arfan Stricker, Bruno H. Kors, Jan A. de Maat, Moniek P. M. de Groot, Natasja M. S. Kavousi, Maryam |
author_facet | Tilly, Martijn J. Lu, Zuolin Geurts, Sven Ikram, M. Arfan Stricker, Bruno H. Kors, Jan A. de Maat, Moniek P. M. de Groot, Natasja M. S. Kavousi, Maryam |
author_sort | Tilly, Martijn J. |
collection | PubMed |
description | BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. METHODS: Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. RESULTS: We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. CONCLUSION: We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. GRAPHICAL ABSTRACT: [Image: see text] |
format | Online Article Text |
id | pubmed-10241730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-102417302023-06-07 Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study Tilly, Martijn J. Lu, Zuolin Geurts, Sven Ikram, M. Arfan Stricker, Bruno H. Kors, Jan A. de Maat, Moniek P. M. de Groot, Natasja M. S. Kavousi, Maryam Clin Res Cardiol Original Paper BACKGROUND: Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. METHODS: Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. RESULTS: We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. CONCLUSION: We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. GRAPHICAL ABSTRACT: [Image: see text] Springer Berlin Heidelberg 2022-08-10 2023 /pmc/articles/PMC10241730/ /pubmed/35948741 http://dx.doi.org/10.1007/s00392-022-02071-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Tilly, Martijn J. Lu, Zuolin Geurts, Sven Ikram, M. Arfan Stricker, Bruno H. Kors, Jan A. de Maat, Moniek P. M. de Groot, Natasja M. S. Kavousi, Maryam Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title | Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title_full | Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title_fullStr | Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title_full_unstemmed | Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title_short | Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study |
title_sort | atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the rotterdam study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241730/ https://www.ncbi.nlm.nih.gov/pubmed/35948741 http://dx.doi.org/10.1007/s00392-022-02071-6 |
work_keys_str_mv | AT tillymartijnj atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT luzuolin atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT geurtssven atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT ikrammarfan atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT strickerbrunoh atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT korsjana atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT demaatmoniekpm atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT degrootnatasjams atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy AT kavousimaryam atrialfibrillationpatternsandtheircardiovascularriskprofilesinthegeneralpopulationtherotterdamstudy |